How Big Data Supports Value-Based Selling
Technology vendors are promoting big data as an innovative way to improve sales force productivity. However, as with other promising sales productivity tools, the greatest driver of value from this innovation often isn't the data or even the insights it can provide, but rather the ability of first-line sales managers (FLMs) to help sales representatives apply these insights to enhance value-based selling.
Any time a new tool is introduced into the sales organization, the sales manager must believe in it and show salespeople how to gain value from it. Big data is just the latest example. For big data to have an impact on sales productivity, FLMs must coach salespeople to apply customer insights to understand customers' needs, communicate the value of the solution in customer terms, and then ensure that customers realize value from the solution.
Big Data, Big Promises
The promise of big data is the quantity and quality of insights it can provide to help sales organizations increase productivity and effectiveness, and, ultimately, generate more revenue. Big data tools are designed to organize data, extract insights, improve data visualization, and increase users' ability to interact with data. This interaction, in turn, improves the sales teams' ability to identify key influencers associated with a particular opportunity and gives the team a sharper perspective on which products and services prospects are likely to buy and which customers are more likely to renew, upgrade, or buy more.
Big data can provide sales organizations with insights into the business problems their customers are trying to address. These fact-based insights can help sales teams nurture leads more effectively and enable sales professionals to align value propositions with customer and prospect needs.
As an example, social media monitoring tools can improve the sales organization's ability to monitor marketplace trends and respond to changes in customer needs and attitudes. For instance, if a customer asks questions about a service or product on a social network, sharing this information with the sales team can place reps in a stronger position to address the customer's needs—but only if salespeople receive this information in a timely manner.
These are some of the promises of big data, but there is also a lot of hype. The tools by themselves won't generate the insight or take the action required of that insight. Moreover, in many cases, the data itself can be misleading. As more and more data is generated, the sales team must ensure the veracity of the data before taking action.
Big data, by itself, only provides that—data. What's going to drive additional insight and sales force effectiveness are processes for organizing data, analytics capabilities to mine that data, and perhaps most importantly, the ability of FLMs to help their sales teams apply those insights.
As companies are better able to understand their customers' businesses, FLMs also have to improve the competencies of their sales professionals to approach prospects and customers with relevant information.
An organization that simply says "We have this data and we're going to send it to the field" is going to reduce sales force productivity because salespeople are not going to know what to do with this greater volume of information.
The FLM has to coach—or better yet, apprentice—the sales team on how to take full advantage of the insight to improve customer engagement. This involves training reps to communicate effectively, initiate discussions with customers and prospects, and provide the appropriate content to address customer needs.
Companies with a sales model based on highlighting features and benefits must be able to change their focus to address business issues. FLMs who are not able to make this shift—and reinforce the appropriate competencies through coaching and on-the-job sales training—will not be able to take full advantage of big data's potential insights.
Achieving these goals also depends on the sales manager understanding and accepting the value of big data tools. If FLMs view big data as no more than today's tech fad, they are less likely to invest time and effort to understand the tools, let alone coach their sales representatives in their use.
Applying big data effectively starts with defining the organization's objectives clearly. One common mistake in big data implementation is making a large investment of time and money without specifying organizational objectives or understanding how it can improve FLMs' ability to help sales professionals address customer needs, overcome objections, and reach key influencers.
Organizations also have to guard against treating big data as a technology play exclusively. If they pursue initiatives without thinking through various use cases, the information they receive will be less valuable, and they will be unable to establish or apply insights.
Companies must deliver timely and relevant insights that support the sales process and align with how salespeople engage customers and prospects. For example, big data should provide new insights that help FLMs identify appropriate content for specific customer scenarios. These insights should be shared via tools already used in the sales organization for account and call planning and collaboration. These tools are increasingly mobile, so organizations may want to start thinking in terms of "mobile first."
Big data by itself is not the answer. Without appropriate coaching from FLMs, big data and its associated tools will become more of a hindrance than an enabler of additional sales force productivity.
Successful sales organizations understand the goal is not simply more data, but providing field representatives with timely and relevant insights about customer and prospect needs. The managers who build winning sales teams will be FLMs who enable salespeople to apply big data's insights effectively through coaching and training. These FLMs will reference and reinforce skills and behaviors that characterize successful value-based selling.
Ashish Vazirani is a managing principal at ZS Associates and leader of the firm’s high-tech practice. A 15-year consulting and sales and marketing management industry veteran, he has led major sales and marketing organization transformations and large engagements with global technology and healthcare leaders.